| Problem 1 |
| Create a New Project called Class1220 to classify numbers that are divisible by 12, divisible by 20 or prime (You must select: Multi-layer Network and Classification in the New Project Dialog). Edit the BuildTrainSet.lab file to build an appropriate training set for the classification of the numbers that are divisible by 12, divisible by 20 or prime. Use the number from 0 to 511 (9 bits). The input training set must include 16 times each number. The classifier must be able to tolerate 10% of noise in the inputs. If a number is divisible by 12 and by 20, set the class to one. Do not get discourage if you do not get the results shown, this problem requires a lot of adjusting, testing and time. |
| Problem 2 |
| Edit the BuilValidSet.lab file to build an appropriate validation set for problem 1. Edite el archivo BuilValidSet.lab para crear un conjunto de validación apropiado para el problema 1. |
| Problem 3 |
| Edit the Train.lab file to design and train an ANN for the classification of numbers. Use one hidden layer and adjust the number of neurons in this layer. Train the ANN appropriately. |
| Problem 4 |
| Edit the CheckTraining.lab file to check the training: (a) Compute the confusion matrix using the training set. (b) Plot the error for each network output. (c) Save the confusion matrix as a vector image (trainConf.emf). |
| Problem 5 |
| Edit the Validation.lab file to perform the validation of the ANN. (a) Compute the confusion matrix using the validation set. (b) Plot the error for each network output. (c) Save the confusion matrix as a vector image (validConf.emf). |
| Problem 6 |
| Generate a report in Microsoft Word. Write some conclusions in the report focusing on the problems that were faced during the simulation and how these problems were or could be solved. |